Paper Citation Record · LEDGER

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge

As of 8 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 1 inbound Pith citation observation for arXiv:2506.01458.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.01458 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:49:24.664062Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:49:21.166909Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-07T11:49:24.836130Z

Reference resolution

28 of 28 outbound references displayed

verified exact2
verified fuzzy23
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7a4d520f-72a6-4b2b-97a2-5cd5e6c31001 · outbound

This paper cites an unresolved cited work.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:49:30.878439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b2cb1467-d847-48e1-a8a9-6f0abf7f6aac · outbound

This paper cites TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:49:24.965664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2ee16bcd-4ebf-4b32-872e-a268d9c90874 · outbound

This paper cites This dataset combines various multilingual speech corpora and covers 141 of the 153 target languages.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge This dataset combines various multilingual speech corpora and covers 141 of the 153 target languages

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:30.650718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 474a6aeb-65c2-48f4-8995-b74b68da9bb3 · outbound

This paper cites hierarchy.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge hierarchy

Reference 4

Resolution: verified exact; doi, observed 2026-08-07T11:49:30.493767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bbe0446c-5d4d-4d45-b19f-ac60080c32ca · outbound

This paper cites an unresolved cited work.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:49:30.342859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 69f8f336-7b9a-4707-8440-348fe06f3643 · outbound

This paper cites an unresolved cited work.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:49:30.194431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f9400ba1-b4c9-4804-8fac-58c53ce60475 · outbound

This paper cites SUPERB: speech processing universal performance benchmark,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge SUPERB: speech processing universal performance benchmark,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:30.028954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f9c7315e-d2d9-423e-a3ef-8bc2f2ff4319 · outbound

This paper cites Seamless: Multilingual expressive and streaming speech translation,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Seamless: Multilingual expressive and streaming speech translation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:29.812930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 95c24d7b-7ac1-45ff-9961-0df48ac5952f · outbound

This paper cites Multi-resolution multi-head attention in deep speaker embedding,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Multi-resolution multi-head attention in deep speaker embedding,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:29.540844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8705feac-87c5-4c4a-bdb5-a16f8092e177 · outbound

This paper cites V oxLingua107: a dataset for spoken lan- guage recognition,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge V oxLingua107: a dataset for spoken lan- guage recognition,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:29.311785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2609b04f-fc89-4d98-80f8-1fac220cd5f2 · outbound

This paper cites A study on data augmentation of reverberant speech for robust speech recognition,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge A study on data augmentation of reverberant speech for robust speech recognition,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:28.992074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 25c88bf8-de74-4f32-9236-12d365b412af · outbound

This paper cites Language identification using phone- based acoustic likelihoods,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Language identification using phone- based acoustic likelihoods,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:28.704376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3d3745ab-bbc6-48c0-8855-4d399a1bfcdc · outbound

This paper cites Language identification using phoneme recog- nition and phonotactic language modeling,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Language identification using phoneme recog- nition and phonotactic language modeling,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:28.442803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a790ebf8-566d-47aa-9984-e10d3fbde980 · outbound

This paper cites Improving language identification of accented speech,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Improving language identification of accented speech,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:28.066366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 15a6f7a1-d75a-4557-9a97-8576212a065e · outbound

This paper cites Scaling a simple approach to zero-shot speech recognition,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Scaling a simple approach to zero-shot speech recognition,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:27.803459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0dfbb53f-fec2-4ec1-95ed-657695391ac1 · outbound

This paper cites Out-of-the-box universal Romanization tool uroman,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Out-of-the-box universal Romanization tool uroman,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:27.600423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f90940b3-7034-42fd-982a-ebe1046369ca · outbound

This paper cites GlotLID: Language identification for low-resource languages,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge GlotLID: Language identification for low-resource languages,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:27.470196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8d297d47-e997-4e09-b87f-fe1ef4badffb · outbound

This paper cites Subword regularization: Improving neural network translation models with multiple subword candidates,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Subword regularization: Improving neural network translation models with multiple subword candidates,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:27.345537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 63d9bfa4-89cd-4d53-a330-005985e39b43 · outbound

This paper cites Leveraging the multilingual Indone- sian ethnic languages dataset in self-supervised models for low- resource ASR task,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Leveraging the multilingual Indone- sian ethnic languages dataset in self-supervised models for low- resource ASR task,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:27.213631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 35be5e7f-1989-4574-bf09-5ffd5b0bdf78 · outbound

This paper cites Thai dialect corpus and transfer-based curriculum learning investigation for dialect automatic speech recognition,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Thai dialect corpus and transfer-based curriculum learning investigation for dialect automatic speech recognition,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:27.045368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2363b6a5-ea45-4dba-aa76-5baf943b8ede · outbound

This paper cites Sim- inchik: A speech corpus for preservation of Southern Quechua,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Sim- inchik: A speech corpus for preservation of Southern Quechua,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:26.873852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation af3d033a-f58c-4fd4-9c3c-615e06029153 · outbound

This paper cites Building large mono- lingual dictionaries at the Leipzig corpora collection: From 100 to 200 languages,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Building large mono- lingual dictionaries at the Leipzig corpora collection: From 100 to 200 languages,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:26.767337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 147d3d7b-5fc8-45db-927f-d38e0cea0b81 · outbound

This paper cites Leveraging end-to-end ASR for endangered language documentation: An empirical study on Yol´oxochitl Mixtec,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Leveraging end-to-end ASR for endangered language documentation: An empirical study on Yol´oxochitl Mixtec,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:26.570624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e4d6c384-0dc2-4128-836a-594e9a3c2e2c · outbound

This paper cites Crowd-sourced speech corpora for Javanese, Sundanese, Sinhala, Nepali, and Bangladeshi Bengali,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Crowd-sourced speech corpora for Javanese, Sundanese, Sinhala, Nepali, and Bangladeshi Bengali,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:26.312079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e79af21f-f35d-4cac-8427-9a4b1fe6d024 · outbound

This paper cites Combining spectral and self-supervised features for low resource speech recognition and translation,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Combining spectral and self-supervised features for low resource speech recognition and translation,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:26.059253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation aca36f3c-c618-4675-9b65-221426767f37 · outbound

This paper cites Scaling speech technology to 1,000+ languages,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Scaling speech technology to 1,000+ languages,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:25.887686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3b96afd8-3314-46ba-8a07-314b0cfcad57 · outbound

This paper cites Espnet: End-to-end speech processing toolkit,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Espnet: End-to-end speech processing toolkit,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:25.583731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0f9b6853-c1be-4b72-8756-c881aea40997 · outbound

This paper cites Dynabench: Rethinking benchmarking in NLP,.

TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge Dynabench: Rethinking benchmarking in NLP,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:49:25.314736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

Observation b2cb1467-d847-48e1-a8a9-6f0abf7f6aac · inbound